Category Using gret l for Principles of Econometrics, 4th Edition

Fulton Fish Example

The following script estimates the reduced form equations using least squares and the demand equation using two-stage least squares for Graddy’s Fulton Fish example.

In the example, ln(quan) and ln(price) are endogenously determined. There are several potential instruments that are available. The variable stormy may be useful in identifying the demand equation. In order for the demand equation to be identified, there must be at least one variable available that effectively influences the supply of fish without affecting its demand. Presumably, stormy weather affects the fishermen’s catch without affecting people’s appetite for fish! Logically, stormy may be a good instrument.

The model of demand includes a set of indicator variables for day of the week...

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Standard Errors and Confidence Intervals for Marginal Effects

Obtaining confidence intervals for the marginal effects (and the AME) is relatively straightfor­ward as well. To estimate the standard error of the marginal effect, we resort to the Delta method. This method of finding the variance of functions of parameters was discussed in section 5.3.2. You may want to take a look at this section again (page 99), before proceeding.

Using the Delta method means taking analytic or numerical derivatives of the marginal effect or AME to be used in the computation of the standard error of the AME. The analytic derivatives are not that hard to take, but why bother when numerical ones are available. This is the approach taken in commercial software that includes the ability to estimate nonlinear combinations of parameters and their standard errors.

The functi...

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Series Plots—Constant and Trends

Our initial impressions of the data are gained from looking at plots of the two series. The data plots are obtained in the usual way after importing the dataset. The data on U. S. and Australian GDP are found in the gdp. gdt file and were collected from 1970:1 – 2004:4.[76] Open the data and set the data structure to quarterly time-series using the setobs 4 command, start the series at 1970:1, and use the —time-series option.

open "@gretldirdatapoegdp. gdt" setobs 4 1970:1 —time-series

One purpose of the plots is to help you determine whether the Dickey-Fuller regressions should contain constants, trends or squared trends. The simplest way to do this is from the console using the scatters command.

scatters usa diff(usa) aus diff(aus)

The scatters command produces multiple graphs, each ...

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Some Statistical Concepts

The hip data are used to illustrate computations for some simple statistics in your text.

C.1 Summary Statistics

Using a script or operating from the console, open the hip data, hip. gdt, and issue the summary command. This yields the results shown in Table C.1. This gives you the mean, median, mini­Summary Statistics, using the observations 1-50 for the variable ‘y’ (50 valid observations)

Mean

Median

Minimum

Maximum

Standard deviation C. V.

Skewness Ex. kurtosis

Table C.1: Summary statistics from the hip data

mum, maximum, standard deviation, coefficient of variation, skewness and excess kurtosis of your variable(s). Once the data are loaded, you can use gretl’s language to generate these as well. For instance, scalar y_bar = mean(y) yields the mean of the variable y...

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Pooling Time-Series and Cross-Sectional Data

A panel of data consists of a group of cross-sectional units (people, firms, states or countries) that are observed over time. Following Hill et al. (2011) we will denote the number of cross-sectional units by N and the number of time periods we observe them as T.

In order to use the predefined procedures for estimating models using panel data in gretl you have to first make sure that your data have been properly structured in the program. The dialog boxes for assigning panel dataset structure using index variables is shown below:

Panel data (stacked time series)

716 cross-sectional units observed over 5

о iUse index variab es

To use this method, the data have to include variables that identify each individual and time period...

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COMBINING DOCUMENTS

You may combine the Document with other documents released under this License, under the terms defined in section 4 above for modified versions, provided that you include in the combination all of the Invariant Sections of all of the original documents, unmodified, and list them all as Invariant Sections of your combined work in its license notice, and that you preserve all their Warranty Disclaimers.

The combined work need only contain one copy of this License, and multiple identical Invariant Sections may be replaced with a single copy...

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